


'''simple docstring'''


import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union

import flax
import jax.numpy as jnp

from ..utils import BaseOutput


UpperCAmelCase_						:  List[Any]				  =						'scheduler_config.json'





class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							A_				: Union[str, Any]       =    1
							A_				: Any       =    2
							A_				: Dict       =    3
							A_				: List[Any]       =    4
							A_				: int       =    5





@dataclass
class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							A_				: jnp.ndarray





class        lowercase__    :





							'''simple docstring'''


							A_				: Optional[Any]       =    SCHEDULER_CONFIG_NAME
							A_				: Optional[Any]       =    ["""dtype"""]
							A_				: Optional[int]       =    []
							A_				: Union[str, Any]       =    True






							@classmethod
							def UpperCAmelCase_      (       cls       ,   __snake_case = None       ,   __snake_case = None       ,   __snake_case=False       ,   **__snake_case       ,   ):
											_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Optional[int]							= cls.load_config(
											    pretrained_model_name_or_path=__snake_case       ,   subfolder=__snake_case       ,   return_unused_kwargs=__snake_case       ,   **__snake_case       ,   )
											_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Optional[int]							= cls.from_config(__snake_case       ,   return_unused_kwargs=__snake_case       ,   **__snake_case    )

											if hasattr(__snake_case       ,   """create_state"""    ) and getattr(__snake_case       ,   """has_state"""       ,   __snake_case    ):
															_SCREAMING_SNAKE_CASE					:			List[str]							= scheduler.create_state()

											if return_unused_kwargs:
															return scheduler, state, unused_kwargs

											return scheduler, state






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = False       ,   **__snake_case    ):
											self.save_config(save_directory=__snake_case       ,   push_to_hub=__snake_case       ,   **__snake_case    )






							@property
							def UpperCAmelCase_      (       self    ):
											return self._get_compatibles()






							@classmethod
							def UpperCAmelCase_      (       cls    ):
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= list(set([cls.__name__] + cls._compatibles    )    )
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= importlib.import_module(__name__.split("""."""    )[0]    )
											_SCREAMING_SNAKE_CASE					:			str							= [
											    getattr(__snake_case       ,   __snake_case    ) for c in compatible_classes_str if hasattr(__snake_case       ,   __snake_case    )
											]
											return compatible_classes







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				assert len(SCREAMING_SNAKE_CASE__	) >= x.ndim
				return jnp.broadcast_to(x.reshape(x.shape + (1,) * (len(SCREAMING_SNAKE_CASE__	) - x.ndim)	)				, SCREAMING_SNAKE_CASE__	)







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__=0.9_9_9				, SCREAMING_SNAKE_CASE__=jnp.floataa	):







				"""simple docstring"""





				def alpha_bar(SCREAMING_SNAKE_CASE__	):
								return math.cos((time_step + 0.0_0_8) / 1.0_0_8 * math.pi / 2	) ** 2

				_SCREAMING_SNAKE_CASE					:			Any							= []
				for i in range(SCREAMING_SNAKE_CASE__	):
								_SCREAMING_SNAKE_CASE					:			Optional[Any]							= i / num_diffusion_timesteps
								_SCREAMING_SNAKE_CASE					:			Tuple							= (i + 1) / num_diffusion_timesteps
								betas.append(min(1 - alpha_bar(SCREAMING_SNAKE_CASE__	) / alpha_bar(SCREAMING_SNAKE_CASE__	)				, SCREAMING_SNAKE_CASE__	)	)
				return jnp.array(SCREAMING_SNAKE_CASE__				, dtype=SCREAMING_SNAKE_CASE__	)





@flax.struct.dataclass
class        lowercase__    :





							'''simple docstring'''


							A_				: jnp.ndarray
							A_				: jnp.ndarray
							A_				: jnp.ndarray






							@classmethod
							def UpperCAmelCase_      (       cls       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= scheduler.config

											if config.trained_betas is not None:
															_SCREAMING_SNAKE_CASE					:			Optional[int]							= jnp.asarray(config.trained_betas       ,   dtype=scheduler.dtype    )
											elif config.beta_schedule == "linear":
															_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= jnp.linspace(config.beta_start       ,   config.beta_end       ,   config.num_train_timesteps       ,   dtype=scheduler.dtype    )
											elif config.beta_schedule == "scaled_linear":
															# this schedule is very specific to the latent diffusion model.
															_SCREAMING_SNAKE_CASE					:			Dict							= (
															    jnp.linspace(
															        config.beta_start**0.5       ,   config.beta_end**0.5       ,   config.num_train_timesteps       ,   dtype=scheduler.dtype    )
															    ** 2
															)
											elif config.beta_schedule == "squaredcos_cap_v2":
															# Glide cosine schedule
															_SCREAMING_SNAKE_CASE					:			Optional[Any]							= betas_for_alpha_bar(config.num_train_timesteps       ,   dtype=scheduler.dtype    )
											else:
															raise NotImplementedError(
															    f"""beta_schedule {config.beta_schedule} is not implemented for scheduler {scheduler.__class__.__name__}"""    )

											_SCREAMING_SNAKE_CASE					:			List[str]							= 1.0 - betas

											_SCREAMING_SNAKE_CASE					:			List[Any]							= jnp.cumprod(__snake_case       ,   axis=0    )

											return cls(
											    alphas=__snake_case       ,   betas=__snake_case       ,   alphas_cumprod=__snake_case       ,   )







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			int							= state.alphas_cumprod

				_SCREAMING_SNAKE_CASE					:			List[Any]							= alphas_cumprod[timesteps] ** 0.5
				_SCREAMING_SNAKE_CASE					:			Dict							= sqrt_alpha_prod.flatten()
				_SCREAMING_SNAKE_CASE					:			List[str]							= broadcast_to_shape_from_left(SCREAMING_SNAKE_CASE__				, original_samples.shape	)

				_SCREAMING_SNAKE_CASE					:			Tuple							= (1 - alphas_cumprod[timesteps]) ** 0.5
				_SCREAMING_SNAKE_CASE					:			List[str]							= sqrt_one_minus_alpha_prod.flatten()
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= broadcast_to_shape_from_left(SCREAMING_SNAKE_CASE__				, original_samples.shape	)

				return sqrt_alpha_prod, sqrt_one_minus_alpha_prod







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Any							= get_sqrt_alpha_prod(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= sqrt_alpha_prod * original_samples + sqrt_one_minus_alpha_prod * noise
				return noisy_samples







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Optional[Any]							= get_sqrt_alpha_prod(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE					:			Optional[int]							= sqrt_alpha_prod * noise - sqrt_one_minus_alpha_prod * sample
				return velocity








'''simple docstring'''


import numpy as np





class        lowercase__    :





							'''simple docstring'''


							def __init__(       self    ):
											_SCREAMING_SNAKE_CASE					:			List[Any]							= (0, 0)
											_SCREAMING_SNAKE_CASE					:			List[str]							= None
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= 0
											_SCREAMING_SNAKE_CASE					:			List[str]							= 0
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= 0






							def __eq__(       self       ,   __snake_case    ):
											return self.position == cell.position






							def UpperCAmelCase_      (       self    ):
											print(self.position    )





class        lowercase__    :





							'''simple docstring'''


							def __init__(       self       ,   __snake_case=(5, 5)    ):
											_SCREAMING_SNAKE_CASE					:			str							= np.zeros(__snake_case    )
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= world_size[0]
											_SCREAMING_SNAKE_CASE					:			Tuple							= world_size[1]






							def UpperCAmelCase_      (       self    ):
											print(self.w    )






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= [
											    (-1, -1),
											    (-1, 0),
											    (-1, 1),
											    (0, -1),
											    (0, 1),
											    (1, -1),
											    (1, 0),
											    (1, 1),
											]
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= cell.position[0]
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= cell.position[1]
											_SCREAMING_SNAKE_CASE					:			Tuple							= []
											for n in neughbour_cord:
															_SCREAMING_SNAKE_CASE					:			Optional[Any]							= current_x + n[0]
															_SCREAMING_SNAKE_CASE					:			List[Any]							= current_y + n[1]
															if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																			_SCREAMING_SNAKE_CASE					:			Optional[int]							= Cell()
																			_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= (x, y)
																			_SCREAMING_SNAKE_CASE					:			Dict							= cell
																			neighbours.append(__snake_case    )
											return neighbours







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Tuple							= []
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= []
				_open.append(SCREAMING_SNAKE_CASE__	)

				while _open:
								_SCREAMING_SNAKE_CASE					:			Any							= np.argmin([n.f for n in _open]	)
								_SCREAMING_SNAKE_CASE					:			List[Any]							= _open[min_f]
								_closed.append(_open.pop(SCREAMING_SNAKE_CASE__	)	)
								if current == goal:
												break
								for n in world.get_neigbours(SCREAMING_SNAKE_CASE__	):
												for c in _closed:
																if c == n:
																				continue
												_SCREAMING_SNAKE_CASE					:			Optional[int]							= current.g + 1
												_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			List[Any]							= n.position
												_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			List[str]							= goal.position
												_SCREAMING_SNAKE_CASE					:			Dict							= (ya - ya) ** 2 + (xa - xa) ** 2
												_SCREAMING_SNAKE_CASE					:			Any							= n.h + n.g

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE					:			Any							= []
				while current.parent is not None:
								path.append(current.position	)
								_SCREAMING_SNAKE_CASE					:			List[Any]							= current.parent
				path.append(current.position	)
				return path[::-1]


if __name__ == "__main__":
				UpperCAmelCase_						:  List[Any]				  =						Gridworld()
				# Start position and goal
				UpperCAmelCase_						:  Optional[Any]				  =						Cell()
				UpperCAmelCase_						:  Tuple				  =						(0, 0)
				UpperCAmelCase_						:  Optional[Any]				  =						Cell()
				UpperCAmelCase_						:  Tuple				  =						(4, 4)
				print(F"path from {start.position} to {goal.position}")
				UpperCAmelCase_						:  Union[str, Any]				  =						astar(world, start, goal)
				#   Just for visual reasons.
				for i in s:
								UpperCAmelCase_						:  Optional[int]				  =						1
				print(world.w)




